Title: Decision maker friendly approach for pricing software

Authors: Ajay K. Aggarwal, Dinesh S. Dave

Addresses: Else School of Management, Millsaps College, Jackson, Mississippi 39210, USA. ' Department of Computer Information Systems, John A Walker College of Business, Appalachian State University, Boone, NC 28608, USA

Abstract: Techniques for predicting computer software prices are of interest to researchers. This paper reviews and extends the earlier contributions of the authors to the field. It illustrates a new approach for predicting software prices. The illustrated approach is superior to previous approaches in two ways. First, the authors employ a unique factoring technique based on variable context that makes the final results easy to interpret and use. Second, the authors use variable transformations that have worked successfully in pricing computer hardware. The paper discusses the model construction, accuracy and results and helps decision makers better understand and control software prices.

Keywords: statistical software; software pricing; artificial intelligence; neural networks; price prediction.

DOI: 10.1504/IJCAT.2009.026671

International Journal of Computer Applications in Technology, 2009 Vol.36 No.1, pp.60 - 66

Published online: 22 Jun 2009 *

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